Evaluating the Applicability of PERSIANN-CDR Products in Drought Monitoring: A Case Study of Long-Term Droughts over Huaihe River Basin, China

Round 1

Reviewer 1 Report

This article presents a study to evaluate the performance of Precipitation Estimation from Remotely Sensed information using Artifical Neural Networks-Climate Data Record (PERSIANN-CDR) to understand the spatiotemporal distribution of drought events in the HuaiHe River Basin, China. Additionally, they have used the Standard Precipitation Index (SPI) to assess the drought in the region. The authors also tested the performance of the PERSIANN-CDR product against the rain gauges observation using performance metrics (CC, RMSE, POD and FAR).

Personally, I think the topic is potentially interesting for the reader and will also be useful to the resource management planner and the scientific community to better understand the extent and impacts of drought.

The MS can be considered for publication after a major revision.


1.  The introduction need to be revised: it does not indicate the shortcomings of current research and the innovations of this paper. Please discuss recent advances in satellite based assessment of meteorological parameters and drought (also discuss their limitations); How is your approach more effective than the other (discuss advantages, disadvantages and limitations)??? Different drought index and its limitation. The literature review is not well done, please cite recent works. 
2. Please incorporate details about the study area, such as hydrogeomorphological feature, drainage pattern, hydrogeology, etc.
3. Please strengthen the methodology, data analysis and discussion part. Authors should revise the MS in a way that attract international readership.
4.    In a separate section, they should discuss about the data preprocessing.
5. A schematic diagram of the methodology flow chat should be incorporated.
6.  The conceptual framework of the study should be presented in detail..
7.    If possible, please discuss the drought trend analysis and risk assessment.
8.    Please include a spatial correlation map (PERSIANN-CDR product against rain gauge observation).
9.  What about the changes in the precipitation amount/rate during different season? Please discuss..
10.    How did you estimate the SPI? Please discuss in text for the reader..
11.  An article should have a maximum references to support the statements. They should include more references……
12.  Please do uncertainty analysis….and also discuss the shortcoming and limitation.
13.  Few grammatical and typographic errors have been noted. Please correct it.

Author Response

We thank you for the positive and constructive comments. We have improved the quality of this paper by accounting for these comments. Our detailed responses are listed in the attached document. Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Line 11. Start by briefly stating the problem.

Line 21. (3, 6 and 12 months).

Line 30. The last sentence should be deleted.

Line 32. the words are repetition of the title. To improve.

The bibliographical reference is not mentioned (21).

Line 55. public instead of pubic.

The variable M is repeated in equations 3 and 5. Change in one of them.

Figure 2. Says "...false positive rate (POD)...". Change.

Figure 9. Says PERISANN. Change.

Do periods of drought coincide with crop cycles? Mention in the text.

Author Response

We thank you for the positive and constructive comments. We have improved the quality of this paper by accounting for these comments. Our detailed responses are listed in the attached document. Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

In their manuscript, Yang et al. study manifestations of meteorological droughts in eastern China, primarily comparing data provided by PERSIANN-CDR (a global, satellite-based precipitation dataset) and observational records from a dense network of meteorological stations in the Huaihe River Basin. Using several validation statistics, agreement between the two datasets is evaluated for different categories of precipitation events, as well as for standardized precipitation index (SPI) at several time scales. Furthermore, representation of three particular historical drought episodes by PERSIANN-CDR is discussed.

 

The manuscript conveys some interesting results, and it seems topically suitable for the Remote Sensing journal. There are, however, certain aspects of the analysis design and presentation that should be improved before the paper can be published - in particular, better description and documentation of the methodology applied is needed (see below for specific suggestions). Moreover, there are numerous typos and grammar inconsistencies throughout the text, severely reducing its readability – additional English editing is strongly recommended.

 

Main comments/suggestions:

(C1): Primary focus of the manuscript is on comparing the PERSIANN-CDR data (dataset defined on a regular longitude-latitude grid) with the gauge-based observations (irregularly spaced, with different sites representing differently sized neighborhoods). However, it is not clear what algorithm was used to match these two types of data. Was, for instance, some form of spatial interpolation applied? Or perhaps area-weighted averaging? Since this can have profound effect on the results, it should be described in the text.

(C2): Pearson correlation coefficient was used as one of the validation statistics. While this is a good choice for Gaussian-distributed data (such as SPI values), it was also employed in analysis of monthly precipitation sums (l. 155). Since such data are potentially non-Gaussian (and other forms of correlation may be more suitable), the authors should consider including an explanation of this choice.

(C3):  Definition of False Alarm Rate (Eq. 4) seems to somewhat differ from its usual form (e.g.  Jolliffe & Stephenson, ISBN 0470864419, p. 46): Specifically, number of hits is used in the denominator rather than number of correct negatives). Is this intentional? Also, the corresponding acronym (FAR) is misspelled in Eq. 4, and term ‘false positive rate’ is used instead in Fig. 3 caption.

(C4): Please add a reference to definition of SPI in Sect. 2.3 (so that specific version of the calculation algorithm is communicated to the reader). Furthermore, SPI values are not actually limited to the -3 to 3 interval (as suggested by the formulation at l. 136).

(C5): In Sect. 4.1, SPI-12 is used for analysis of temporal structure of individual drought events. I wonder, however, if a shorter time scale (studied, e.g., through SPI-3 or SPI-1) would not be better to show details in the time series. (I do not necessarily suggest that the authors re-do their analysis, but an explanation of why SPI-12 was used would be helpful).

 

Minor/technical remarks:

·         l. 87+: The chapters are referred to by Roman numerals, but Arabic ones are used in the text.

·         Fig. 1: Why are some of the map symbols in different color? Also, is ‘dem’ terrain elevation? (the abbreviation is not explained).

·         l. 155: Bias is used as one of the validation statistics, but, unlike the rest, it is not introduced in Sect. 2.2.

·    Fig. 2: ‘False positive rate’ is specified in the caption, rather than ‘probability of detection’.

·         Throughout the text, acronyms SPI-3, SPI-6, SPI-12 are sometimes used with dash, sometimes without.

·         p. 12: A non-existent Fig. 19 is referenced.

·         Fig. 14: It might be visually preferable to eliminate the overlap of the text and the color scale.

·    Nash-Sutcliffe coefficient is mentioned in the Abstract (including a specific numerical value), but it is not employed in the text itself.

Author Response

We thank you for the positive and constructive comments. We have improved the quality of this paper by accounting for these comments. Our detailed responses are listed in the attached document. Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Thanks for the response to my comments... The quality of the manuscript is improved considerably.

Author Response

Comment:  Thanks for the response to my comments... The quality of the manuscript is improved considerably.

Response: We thank you for your positive and constructive comments to help us improve this manuscaript.

Reviewer 3 Report

In the revised version of the manuscript, the authors have sufficiently addressed my comments. I would nevertheless recommend another thorough read-through before final typesetting, as there are still some typos in the text.

Author Response

Comment : In the revised version of the manuscript, the authors have sufficiently addressed my comments. I would nevertheless recommend another thorough read-through before final typesetting, as there are still some typos in the text.

Response: Thank you for your valuable suggestions on this article. We checked and corrected those typos in the revised manuscript.